AI-102 Implement computer vision solutions Practice Question
A developer needs to build a mobile app that identifies dog breeds from photos. They have a small dataset of labeled images and want to train a custom model with minimal machine learning expertise. Which Azure service should they use?
⚠ Common exam trap
The trap here is assuming that Azure AI Vision prebuilt models can classify specific breeds, when they only provide generic tags and cannot be customized without Custom Vision.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure AI Custom Vision
Custom Vision is designed for custom image classification and object detection with minimal ML expertise. It supports training on small datasets and provides a user-friendly interface. The other services either require more ML knowledge, offer only prebuilt models, or are for a different domain entirely. Custom Vision directly meets the need to identify dog breeds from photos.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure AI Vision Image Analysis
Why it's wrong here
Image Analysis provides prebuilt models for general image understanding, such as tags and captions, but it cannot be trained to recognize specific dog breeds. It might return generic tags like 'dog' but not the breed. The requirement is to identify specific breeds, which requires a custom model. Therefore, Image Analysis is not suitable for this task.
- ✗
Azure AI Face API
Why it's wrong here
The Face API is designed for human face detection, recognition, and analysis. It cannot identify dog breeds. Using it for this purpose would be completely ineffective. The scenario is about animal classification, not human faces, so the Face API is irrelevant and would not provide any useful functionality.
- ✗
Azure Machine Learning designer
Why it's wrong here
Azure Machine Learning designer is a drag-and-drop tool for building ML pipelines, but it requires more ML knowledge to select algorithms, preprocess data, and tune hyperparameters. While it can train image classification models, it is not as streamlined as Custom Vision for a developer with minimal ML expertise. The scenario emphasizes ease of use and a small dataset, which Custom Vision addresses better.
- ✓
Azure AI Custom Vision
Why this is correct
Custom Vision is a no-code/low-code service that allows you to upload labeled images and train a classification model. It provides a simple interface and SDKs, making it ideal for developers with limited ML expertise. It supports multi-class classification, which is suitable for identifying dog breeds from photos. The service handles training and deployment, so the developer can focus on the app.
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Last reviewed September 2026 · checked against the official Microsoft exam blueprint
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